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Record W2983803118 · doi:10.1182/blood-2019-128302

Impact of Tisagenlecleucel Chimeric Antigen Receptor (CAR)-T Cell Therapy Product Attributes on Clinical Outcomes in Adults with Relapsed or Refractory Diffuse Large B-Cell Lymphoma (r/r DLBCL)

2019· article· en· W2983803118 on OpenAlexaff
Veronika Bachanová, Constantine S. Tam, Peter Borchmann, Ulrich Jaeger, Joseph P. McGuirk, Harald Holte, Edmund K. Waller, Samantha Jaglowski, Michael Bishop, Charalambos Andreadis, S.R. Foley, Jason R. Westin, Isabelle Fleury, P. Joy Ho, Stephan Mielke, Takanori Teshima, Gilles Salles, Stephen J. Schuster, Richard T. Maziarz, Koen van Besien, Koji Izutsu, Marie José Kersten, John Magenau, Nina D. Wagner‐Johnston, Koji Kato, Paolo Corradini, Jufen Chu, Irina Gershgorin, Therese Choquette, Lida Pacaud, Margit Jeschke

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontHamilton Health Sciences
Fundersnot available
KeywordsChimeric antigen receptorDiffuse large B-cell lymphomaMedicineRefractory (planetary science)LymphomaCytokine release syndromeInternal medicineOncologyCancer researchImmunotherapyImmunologyBiologyCancer

Abstract

fetched live from OpenAlex

Background: In the phase 2 JULIET trial, tisagenlecleucel, an anti-CD19 CAR-T cell therapy, demonstrated durable responses and manageable safety in adult patients (pts) with r/r DLBCL. Here, we examine the impact of key product cellular attributes of tisagenlecleucel on clinical outcomes. Methods: JULIET is a single-arm, global, phase 2 trial of tisagenlecleucel in adult pts with r/r DLBCL. Samples from 115 tisagenlecleucel individual products were examined at the end of manufacturing at the batch release testing for various product attributes (Table). Additional detailed immunophenotyping for 66 attributes was conducted on previously frozen product samples via flow cytometry (FC). For each cell population of CAR+ T cells, the percentage and absolute number of the subpopulation were analyzed. Univariate and multivariate analyses were performed to evaluate effects of product attributes and CAR+ T-cell phenotypes on efficacy (Month 3 response [M3R], duration of response [DOR], progression-free survival [PFS], overall survival [OS]) and safety (cytokine release syndrome [CRS] and neurological events [NE], grade 0-2 [low] vs 3-4 [severe]). Several exploratory approaches, including machine learning methods (eg, elastic net and random forest), were pursued in conjunction with logistic regression to identify a set of variables associated with clinical outcomes. We included clinically relevant characteristics evaluated at baseline per protocol (LDH, CRP, and tumor volume) with the product attributes in multivariate modeling. Logistic regression was used to model M3R, CRS, and NE. Cox regression was used to model DOR, PFS, and OS. Results: As of December 11, 2018, 115 pts were infused and evaluable. The median T-cell transduction efficiency by FC was 28% (range, 5.3-63.2%); no relationship of these attributes with efficacy (M3R, DOR, PFS, or OS) or safety (severe CRS or NE) was observed. The percentage of viable cells had no impact on efficacy or safety outcomes; this was anticipated since tisagenlecleucel dose is formulated based on the number of viable CAR+ T cells. Tisagenlecleucel demonstrated in vitro functional activity upon CD19-specific stimulation, as evidenced by IFNγ release, with a wide range among different batches (range, 23.7-938 fg/CAR+ cell). Durable responses were observed across the entire range of IFNγ release; high IFNγ release was not associated with severe CRS or NE. The median ratio of CAR+ CD4+ to CD8+ cells was 3.70 (range, 0.26-65.3); no relationship with clinical outcomes was observed (Figure). CAR+ T cells showed variability in T-cell phenotypes, with central memory (CM) cells as the predominant subpopulation of both CD4+ and CD8+ CAR+ T cells (Figure). The majority of CAR+ T cells were highly activated (co-expressing HLA-DR and CD38), as measured by FC. Relative and absolute number of less mature T cells (naive and CM T cells) in the product did not correlate with efficacy. There was no significant correlation between cell populations and efficacy on multivariate analyses. For CRS, the total number of certain CD4+ T cells expressing activation markers (HLA-DR+, CD25+, or HLA-DR+CD38+) and CM cells showed trends of correlation with more severe CRS, but none of these were significant after p-value adjustment; in a multivariate regression model adjusted for LDH and other clinically relevant factors, HLA-DR+ CD38+CD4+ T cells showed a correlation with severe CRS. Correlation analyses did not reveal product attributes significantly related to severe NE. Conclusions: In JULIET, tisagenlecleucel CAR-T cell product attributes had no significant impact on efficacy or NE; the total number of activated CD4+ cells infused positively correlated with higher-grade CRS. There is great variability in the product attributes, especially with respect to T-cell phenotypes, though this variability appears to play a minor role on efficacy. Additional analyses with larger data sets are required to confirm these findings. ClinicalTrials.gov Identifier: NCT02445248. Disclosures Bachanova: Novartis: Research Funding; Gamida Cell: Research Funding; GT Biopharma: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Incyte: Research Funding. Tam:BeiGene: Honoraria; Janssen: Honoraria, Research Funding; Roche: Honoraria; Novartis: Honoraria; AbbVie: Honoraria, Research Funding. Jaeger:Novartis, Roche, Sandoz: Consultancy; AbbVie, Celgene, Gilead, Novartis, Roche, Takeda Millennium: Research Funding; Amgen, AbbVie, Celgene, Eisai, Gilead, Janssen, Novartis, Roche, Takeda Millennium, MSD, BMS, Sanofi: Honoraria; Celgene, Roche, Janssen, Gilead, Novartis, MSD, AbbVie, Sanofi: Membership on an entity's Board of Directors or advisory committees. McGuirk:Novartis: Research Funding; Fresenius Biotech: Research Funding; Astellas: Research Funding; Bellicum Pharmaceuticals: Research Funding; Kite Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Gamida Cell: Research Funding; Pluristem Ltd: Research Funding; ArticulateScience LLC: Other: Assistance with manuscript preparation; Juno Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Holte:Novartis: Honoraria, Other: Advisory board. Waller:Amgen: Consultancy; Kalytera: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Other: Travel expenses, Research Funding; Cerus Corporation: Other: Stock, Patents & Royalties; Chimerix: Other: Stock; Cambium Oncology: Patents & Royalties: Patents, royalties or other intellectual property . Jaglowski:Juno: Consultancy, Other: advisory board; Kite: Consultancy, Other: advisory board, Research Funding; Novartis: Consultancy, Other: advisory board, Research Funding; Unum Therapeutics Inc.: Research Funding. Bishop:CRISPR Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Andreadis:Celgene: Research Funding; Novartis: Research Funding; Jazz Pharmaceuticals: Consultancy; Roche: Equity Ownership; Pharmacyclics: Research Funding; Merck: Research Funding; Gilead: Consultancy; Kite: Consultancy; Genentech: Consultancy, Employment; Juno: Research Funding. Foley:Celgene: Speakers Bureau; Amgen: Speakers Bureau; Janssen: Speakers Bureau. Westin:Unum: Research Funding; Genentech: Other: Advisory Board, Research Funding; Novartis: Other: Advisory Board, Research Funding; Janssen: Other: Advisory Board, Research Funding; Juno: Other: Advisory Board; Kite: Other: Advisory Board, Research Funding; 47 Inc: Research Funding; Curis: Other: Advisory Board, Research Funding; MorphoSys: Other: Advisory Board; Celgene: Other: Advisory Board, Research Funding. Fleury:Gilead: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; AstraZeneca: Consultancy. Ho:Janssen: Other: Trial Investigator meeting travel costs; Celgene: Other: Trial Investigator meeting travel costs; La Jolla: Other: Trial Investigator meeting travel costs; Novartis: Other: Trial Investigator meeting travel costs. Mielke:Miltenyi: Consultancy, Honoraria, Other: Travel and speakers fee (via institution), Speakers Bureau; DGHO: Other: Travel support; Jazz Pharma: Honoraria, Other: Travel support, Speakers Bureau; EBMT/EHA: Other: Travel support; Celgene: Honoraria, Other: Travel support (via institution), Speakers Bureau; ISCT: Other: Travel support; Bellicum: Consultancy, Honoraria, Other: Travel (via institution); GILEAD: Consultancy, Honoraria, Other: travel (via institution), Speakers Bureau; Kiadis Pharma: Consultancy, Honoraria, Other: Travel support (via institution), Speakers Bureau; IACH: Other: Travel support. Teshima:Novartis: Honoraria, Research Funding. Salles:Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria. Schuster:Celgene: Consultancy, Honoraria, Research Funding; Acerta: Consultancy, Honoraria, Research Funding; Loxo Oncology: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria, Research Funding; Merck: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Nordic Nano

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.335
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations11
Published2019
Admission routes1
Has abstractyes

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